Evolutionary Behaviour Tree Approaches for Navigating Platform Games

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Miguel Nicolau and Diego Perez-Liebana and 
                 Michael O'Neill and Anthony Brabazon",
  title =        "Evolutionary Behaviour Tree Approaches for Navigating
                 Platform Games",
  journal =      "IEEE Transactions on Computational Intelligence and AI
                 in Games",
  year =         "2016",
  volume =       "9",
  number =       "3",
  pages =        "227--238",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, grammatical
  DOI =          "doi:10.1109/TCIAIG.2016.2543661",
  abstract =     "Computer games are highly dynamic environments, where
                 players are faced with a multitude of potentially
                 unseen scenarios. In this paper, AI controllers are
                 applied to the Mario AI benchmark platform, by using
                 the grammatical evolution system to evolve behavior
                 tree structures. These controllers are either evolved
                 to both deal with navigation and reactiveness to
                 elements of the game or used in conjunction with a
                 dynamic A* approach. The results obtained highlight the
                 applicability of behavior trees as representations for
                 evolutionary computation and their flexibility for
                 incorporation of diverse algorithms to deal with
                 specific aspects of bot control in game environments.",
  notes =        "Mario AI",

Genetic Programming entries for Miguel Nicolau Diego Perez-Liebana Michael O'Neill Anthony Brabazon